Can computer-based technology identify the speech changes that occur in early Alzheimer’s?
Neguine Rezaii, M.D.
Massachusetts General Hospital
Boston, MA - United States
Studies have found that subtle changes in speech patterns, such as the rate of one’s speech or length of pauses between words, may be indicative of the early brain changes observed in Alzheimer’s and other dementia that are not easily detectable in clinical settings. This has led to the development of standardized language-based screening tests for Alzheimer’s screening. However, the relationship between changes in speech and the underlying brain changes in Alzheimer’s are not well known. Dr. Neguine Rezaii and colleagues plan to expand our understanding of the early brain changes in Alzheimer’s and their relationship to speech patterns.
For this project, Dr. Rezaii and colleagues will study the relationship between changes in speech patterns and cognitive decline in early Alzheimer’s. They will use an advanced computer science technique called machine learning, a form of artificial intelligence, to examine whether changes in speech alone can detect early signs of Alzheimer’s. The researchers will recruit 100 individuals with Alzheimer’s to participate in the study and 100 age-matched cognitively unimpaired individuals. Lastly, the team will use their machine learning technique to associate changes in speech with amyloid plaque and tau tangle levels, two of the hallmark brain changes in Alzheimer’s, and examine if changes in speech could be used to predict early brain changes in Alzheimer’s.
The results of this study may provide key insight into the language changes that occur during the early stages of Alzheimer’s and may lead to a new non-invasive, low-cost approach for early detection.
Funding support for this project has been made possible by the Fred A. and Barbara M. Erb Family Foundation. This awardee is recognized as the Fred A. Erb Clinical Research Science Fellow for the Alzheimer's Association.
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